A Novel Automated Biodiversity Monitoring and Conservation Information System with Google Earth Engine
Keywords: Google Earth Engine, Biodiversity, Land-Cover-Land-Use Change Detection, Earth Observation.
Abstract: Abstract
Biodiversity entails a vast set of earth’s life, including animals, plants, microorganisms, and organisms underwater. It contains the ecosystem variation, genetic variation, and species in the area, planet, or biome. Lately, both human and natural activities have contributed to biodiversity degradation at an alarming rate. Natural disasters like earthquakes, drought, hurricanes, and floods have significantly contributed to biodiversity disturbance. Biodiversity degradation is attracting the attention of scientists and decision-makers locally and at a global scale because of its importance in the natural reservoir and outstanding economic potential.
Locally, in Kenya, human interference in the ecosystem is greatly felt and its’ effects negatively affect human life, livestock, wildlife, forests, and life underwater. The increased biodiversity degradation is associated with exponential human population growth, declining rainfall, and striking temperature rise. The economic cost of biodiversity loss in Kenya amounts to 1.3 billion dollars annually. The country’s GDP is affected to the extent of 1.3 billion dollars resulting in 4.9%. More than 12 million Kenyans reside in degraded lands. Additionally, Wildlife declined by 68% threatening species extinction and population viability. Livestock numbers declined by 25.2% because of a lack of feed and sufficient water. Approximately 900000, children suffer malnutrition while adults suffer hunger stress resulting from biodiversity destruction.
Complex earth observation systems have been developed to support data and spatially extensive biodiversity research as compared to traditional approaches. Researchers intend to implement a new monitoring approach in Nakuru, Narok, and Baringo counties in Kenya considering their gradual change in biodiversity richness. The selected counties suffer increased soil erosion, agro-biodiversity loss, low productivity, forest loss, water basin reduction, and soil nutrient depletion.
This paper presents a novel approach to biodiversity conservation using remote sensing, and readily available data in Google Earth Engine (GEE) data catalog to develop a real-time monitoring biodiversity tool to classify key aspects, assess the change, and identify major contributing disturbances. Expected results are a real-time online Google Earth Engine application used for biodiversity monitoring for decision support. The researchers present a real-time biodiversity monitoring and restoration intervention tool for conservation, management, and assessment in the selected counties.
Submission Category: Machine learning algorithms
Submission Number: 47
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